Discipline

Engineering, Information, And Communication Technology

Abstract

This study evaluates the utilization of Artificial Intelligence AI in Quality Assurance and Quality Control QA QC practices within the mechanical engineering consultancy industry in the Philippines. As the country advanced toward Industry 4.0, the adoption of AI-based tools for inspection, testing, and predictive maintenance reshaped the consultancy landscape. The research employed a quantitative descriptive design involving 200 respondents from various consultancy firms engaged in mechanical design, project supervision, and plant maintenance. Key input variables included regulatory compliance, qualifications, professional experience, education, character, and ethical considerations that affect AI adoption. The findings indicated that AI significantly enhanced QA QC accuracy, operational efficiency, and compliance reliability. However, challenges persisted regarding cost, training, and the ethical use of AI data. The study aimed to develop an action plan to integrate AI-enabled tools into consultancy operations while reinforcing ethical standards and continuous professional development. The expected outcome was a strategic framework guiding mechanical engineering consultancy firms toward sustainable, technology-driven QA QC excellence.

Keywords

professional development, artificial intelligence, quality assurance and quality control, mechanical engineering consultancy, industry 4.0, ai adoption, ethics